People have increasingly turned to the Internet for the answers to their questions. Such an approach is encouraged by companies; web site support is considerably less expensive than telephone or on-site support. The ability of a company to successfully direct customers, employees and other information seekers to their web site, however, is a function of the amount of success customers expect to meet when they access the site.
In a customer service environment, for example, customers expect prompt and correct answers to their information requests. These information requests may relate to problems with products the customer has purchased, or to questions about products they may decide to purchase in the future. In most cases, the answer to the customer's question exists somewhere within the enterprise. In other cases, the answer may have existed in the enterprise at one time, but is no longer there. The challenge is to find the best answer, helpful content, service, or expert, and to provide it to the customer in a timely manner.
Typical approaches to providing support information to customers on the Internet depend on either a static structure (e.g., predefined hyperlinks) for customers to navigate to the information they need, or simple “lookup” facilities for finding documents or products. Representative “lookup” facilities include database searches and full-text searches for keywords appearing in documents or in product descriptions. These types of approaches are typically not tailored to the additional needed clarifications and the customer (i.e., no personalization) and do not typically engage the customer in a multiple step interaction (no conversational dialog), wherein the information is elicited from the customer.
Other current approaches for providing support information to customers, such as case-based reasoning systems and expert systems, provide a multiple step interaction with customers. They require the business, however, to set up very complex “case” structures or expert-system rule sets that define the problems and their resolutions in great detail. These approaches are often brittle; it is typically very costly for the business to add new rules and cases to these systems.
Still other Web-based systems check for particular textual content without the advantage of context or domain knowledge. Consequently, they generally do not reliably and consistently return the desired information. This is at least partly due to the fact that language is inherently ambiguous. Another factor, however, is because a single concept may be expressed in any number of ways using numerous and unrelated words and/or phrases. By simply searching for specific key words, the typical search engine fails to identify other alternatives that may also be helpful.
U.S. patent application Ser. No. 09/594,083, entitled “System and Method for Implementing a Knowledge Management System,” describes a system and method for parsing documents into a series of concepts and tying the concepts to taxonomies. Queries, too, are parsed into a series of concepts and marked, for instance, with tags reflective of their taxonomy. The query and its tags are then used to search for documents relating to the query. The result is a list of documents which more closely matches the question being asked.
As noted above, the Internet has emerged as a preferred mechanism for making information available in a low cost manner. People both within and external to particular organizations are encouraged to access that organization's web site to retrieve answers to their questions. Ideally, the person accessing the web site receives the correct answer. An organization is, however, incapable of measuring the ability of a user to retrieve the correct answer without the use of metrics to measure satisfactory and unsatisfactory outcomes.
What is needed is a system and method for measuring the quality of information retrieval to help guide an organization's efforts in improving the web self-service system.